Temporal data is data that keeps track of changes over time. It is data, more precisely, that keeps track of changes along either one or two temporal dimensions.
One of these temporal dimensions is called “valid time” by computer scientists. In valid time, modifications to data in a database reflect changes happening in the world around us, and that we wish to keep track of. The second of these two temporal dimensions is called “transaction time” by computer scientists. Transaction time keeps track of when data is initially entered into a database. But in addition, transaction time keeps track of modifications to data in a database that do not reflect anything that is happening in the world around us. Instead, these modifications are made to adjust the data in some way, independent of what is happening to what the data represents. For the most part, these adjustments are made to correct mistakes found in the data.
Attempts to manage temporal data that varies in valid time may be found in many business applications. Research into temporal data that varies in both valid time and transaction time has been ongoing in the computer science community for several decades. Although there is still no de jure SQL standard for managing temporal data, DBMS vendors have begun to add support for temporal data to their DBMSs and related products.